Questions and Answers
What is the primary purpose of data analytics in commercial industries?
To make business decisions and optimize performance
What is the process of gaining valuable insights from data to make effective business decisions called?
Data Analysis
What type of analytics involves using data to predict future outcomes?
Predictive analytics
Who are responsible for performing data analytics tasks?
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What is the term for the process of transforming data into a more usable format?
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What is the primary goal of data visualization?
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What is a crucial requirement for a scale in data visualization?
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What type of scale is suitable for data that exhibits exponential growth?
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What is the purpose of a scale in data visualization?
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What type of coordinate system is commonly used for circular data?
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What is the primary characteristic of the angle axis in the polar coordinate system?
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What is the result of using a scale that is not one-to-one?
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Which type of data analysis involves understanding the relationships between variables?
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What is an example of a data transformation?
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What is the purpose of data transformation in the context of data analysis?
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What is the primary advantage of using logarithmic scales in data visualization?
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What is the main difference between categorical and continuous data?
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What is the coordinate system used to specify positions via an angle and a radial distance from the origin?
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Study Notes
Data Types and Visualization
- A dataset can have various types of data, including:
- Ordered factor (e.g., month)
- Discrete numerical value (e.g., day)
- Unordered factor (e.g., location, station ID)
- Continuous numerical value (e.g., temperature in degrees Fahrenheit)
Data Visualization and Scales
- Scales map data values to aesthetic values (e.g., x-axis positions, shapes, colors)
- A scale must be one-to-one, ensuring a unique mapping between data and aesthetics values
- In polar coordinate systems, positions are specified via an angle and radial distance from the origin
Data Analysis Tasks
- Importing datasets and libraries (e.g., numpy, pandas, matplotlib, seaborn)
- Importing a dataset (e.g., Credit Card Approvals) using
pd.read_csv()
Data Characteristics
- Categorical data: Gender, Married, BankCustomer, Industry, Ethnicity, PriorDefault, Employed, DrivingLicense, Citizen, Approved
- Continuous data: Age, Debt, YearsEmployed, CreditScore, Income
Univariate Analysis
- Univariate analysis is a basic form of data analysis, focusing on a single variable
- Used to understand the data without examining causes or effects relationships
Data Analytics
- Data analytics: the process of analyzing data sets to make informed decisions
- Uses specialized software and systems to help businesses:
- Understand customers better
- Improve advertising campaigns
- Personalize content
- Improve bottom lines
Data Visualization and Analytics
- Data visualization helps gain better insights into data
- Both data visualization and analytics draw conclusions about datasets
- Data visualization can be static or interactive
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Description
Test your understanding of data analytics, its applications, and techniques in commercial industries. Learn how data analytics can help businesses make informed decisions, improve customer understanding, and boost their bottom lines.
